Canonical forms a b s t r a c t Retrieval of 3D shapes is a challenging problem, especially for non-rigid shapes. One approach giving favourable results uses multidimensional scaling (MDS) to compute a canonical form for each mesh, after which rigid shape matching can be applied. However, a drawback of this method is that it requires geodesic distances to be computed between all pairs of mesh vertices. Due to the super-quadratic computational complexity, canonical forms can only be computed for low-resolution meshes. We suggest a linear time complexity method for computing a canonical form, using Euclidean distances between pairs of a small subset of vertices. This approach has comparable retrieval accuracy but lower time complexity than us...
In this paper, we propose a highly efficient metric learning approach to non-rigid 3D shape analysis...
Content-based 3D object retrieval has become an active topic in many research communities. In this p...
This paper presents a new method for 2-D and 3-D shape retrieval based on geodesic signatures. These...
AbstractRetrieval of 3D shapes is a challenging problem, especially for non-rigid shapes. One approa...
Retrieval of 3D shapes is a challenging problem, especially for non-rigid shapes. One approach givin...
Canonical forms attempt to factor out a non-rigid shape's pose, giving a pose-neutral shape. This op...
We present a new benchmark for testing algorithms that create canonical forms for use in non-rigid 3...
Measuring the dissimilarity between non-rigid objects is a challenging problem in 3D shape retrieval...
∗Track organisers We present a new benchmark for testing algorithms that create canonical forms for ...
The retrieval of non-rigid 3D shapes is an important task. A common technique is to simplify this pr...
Large 3D shape repositories are becoming available at present. In computer aided design, computer vi...
We present a scalable and unsupervised approach for content-based retrieval on 3D model collections....
In this paper, we propose a novel approach to learning robust ground distance functions of the Earth...
In this paper, we propose a highly efficient metric learning approach to non-rigid 3D shape analysis...
Content-based 3D object retrieval has become an active topic in many research communities. In this p...
This paper presents a new method for 2-D and 3-D shape retrieval based on geodesic signatures. These...
AbstractRetrieval of 3D shapes is a challenging problem, especially for non-rigid shapes. One approa...
Retrieval of 3D shapes is a challenging problem, especially for non-rigid shapes. One approach givin...
Canonical forms attempt to factor out a non-rigid shape's pose, giving a pose-neutral shape. This op...
We present a new benchmark for testing algorithms that create canonical forms for use in non-rigid 3...
Measuring the dissimilarity between non-rigid objects is a challenging problem in 3D shape retrieval...
∗Track organisers We present a new benchmark for testing algorithms that create canonical forms for ...
The retrieval of non-rigid 3D shapes is an important task. A common technique is to simplify this pr...
Large 3D shape repositories are becoming available at present. In computer aided design, computer vi...
We present a scalable and unsupervised approach for content-based retrieval on 3D model collections....
In this paper, we propose a novel approach to learning robust ground distance functions of the Earth...
In this paper, we propose a highly efficient metric learning approach to non-rigid 3D shape analysis...
Content-based 3D object retrieval has become an active topic in many research communities. In this p...
This paper presents a new method for 2-D and 3-D shape retrieval based on geodesic signatures. These...